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Found 7 result(s)
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This web site provides adjusted and homogenized climate data for many climatological stations in Canada. These data were created for use in climate research including climate change studies. They incorporate a number of adjustments applied to the original station data to address shifts due to changes in instruments and in observing procedures. Sometimes the observations from several stations were joined to generate a long time series. The adjusted and homogenized data are provided for four climate elements: surface air temperature, precipitation, surface pressure, and surface wind speed.
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DIAS aims at collecting and storing earth observation data; analyzing such data in combination with socio-economic data, and converting data into information useful for crisis management with respect to global-scale environmental disasters, and other threats; and to make this information available within Japan and overseas.
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
Country
The National Cryosphere Desert Data Center (hereinafter referred to as NCDC) is supported by the Institute of environment and Engineering in the cold and dry areas of the Chinese Academy of Sciences, in cooperation with Xinjiang Institute of ecology and geography of the Chinese Academy of Sciences, Chengdu Institute of mountain land disaster and environment of the Ministry of water resources of the Chinese Academy of Sciences, Qinghai Salt Lake Research Institute of the Chinese Academy of Sciences and Qinghai Gao of the Chinese Academy of Sciences The Institute of protobiology and other units were jointly established. The supporting units of glacier permafrost desert data center have formed a scientific research and support system of seven research laboratories and three research systems, highlighting the research characteristics of glacier, permafrost, desert, atmosphere, water and soil, ecology, environment, resources, engineering and sustainable development in the dry areas of cold regions.
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SISMER (Scientific Information Systems for the Sea) is Ifremer's service in charge of managing numerous marine databases and information systems which Ifremer is responsible for implementing. The information systems managed by SISMER range from CATDS (SMOS satellite data) to geoscience data (bathymetry, seismics, geological samples), not forgetting water column data (physics and chemistry, data for operational oceanography – Coriolis - Copernicus CMEMS), fisheries data (Harmonie), coastal environment data (Quadrige 2) and deep-sea environment data (Archimède). SISMER therefore plays a pivotal role in marine database management both for Ifremer and for many national, European and international projects.
Data repository of a meteorological experiment conducted in Perdigão, Portugal between December 15, 2016 to June 15, 2017. The Perdigao field project is part of a larger joint US/European multi-year program in Portugal. The project is partially funded by the European Union (EU) ERANET+ to provide the wind energy sector with more detailed resource mapping capabilities in the form of a new digital EU wind atlas. A major goal of the Perdigão field project is to quantify errors of wind resource models against a benchmark dataset collected in complex terrain. The US participation will complement this activity by identifying physical and numerical weaknesses of models and developing new knowledge and methods to overcome such deficiencies.